Risk Forecast Using Hidden Markov Models

  • James D. Cannady
  • , Charles Pak

    Research output: Contribution to journalArticlepeer-review

    Abstract

    Today’s fast moving technologies create innovative ideas, products, and services, but they also bring with them new security risks. The gap between new technologies and the security needed to keep them from opening up new risks in information systems (ISs) can be difficult to close completely. Changes in ISs are inevitable because computing environments, intentionally or unintentionally, are always changing. These changes bring with them vulnerabilities on new or existing ISs, which cause security states to move between mitigated, vulnerable, and compromised states. In previous work, we introduced the near real-time risk assessment using hidden Markov models (HMMs). This paper applies that theory to a prototype MatLab™ environment.

    Original languageAmerican English
    JournalResearch in Information Technology
    Volume7
    DOIs
    StatePublished - Jul 1 2010

    Keywords

    • Hidden Markov Models
    • MatLab™
    • Risk Analysis
    • Risk Assessment
    • Risk Management
    • Simulink®
    • Viterbi Algorithm

    Disciplines

    • Computer Sciences

    Fingerprint

    Dive into the research topics of 'Risk Forecast Using Hidden Markov Models'. Together they form a unique fingerprint.

    Cite this